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RYJOX

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We’ve been experimenting with a new database architecture for real-time AI, robotics, and agent workloads. The prototype in this 90-second demo shows a persistent graph engine that:

delivers 0.12–0.4 µs hot-path reads

stores 50M durable nodes on an 8GB Jetson Orin Nano

streams a 40–50GB graph from NVMe as if it were RAM

maintains ACID guarantees under power-fail/crash tests

uses a hardware-native concurrency lattice instead of locks or B-trees

The goal wasn’t to optimise an existing database, but to test whether durable sub-microsecond access was even possible without keeping the whole graph in memory.

We’re a very early startup exploring this space and would genuinely appreciate critical feedback, collaboration, and technical pushback from people who’ve worked on database internals, kernels, robotics systems, or high-performance storage.

If you see flaws, edge cases, missing failure modes, or things that “shouldn’t work,” we’d love to hear from you.

This made me laugh, just because you have a high IQ does not mean you are granted an easy passage.

CUDA Ontology 8 months ago

Interesting, does this approach change with out-of-order cores? In fact maybe I misunderstand lol